Measuring the ROI of Intent-Based Marketing

Why Intent-Based Marketing Delivers Superior ROI

It Reduces Wasted Spend on Low-Intent Leads

Traditional marketing often targets leads based on static criteria like firmographics or job titles, without knowing if there’s actual buying interest. That approach leads to wasted budget, generic campaigns, and sales teams chasing cold leads. 

Intent-based marketing uses a different approach. Instead of marketing to everyone who could be a fit, you focus only on accounts actively demonstrating interest in your category. 

The keyword here is ‘intent’ —ie., potential customers searching for solutions, comparing vendors, or engaging with topic-relevant content. 

For example, if an account hasn’t engaged with any category-related content in the last six months, continuing to push nurture emails or run ad campaigns is a poor use of resources. 

With intent data, you can suppress or deprioritize these accounts and reallocate budget to those who are surging on key topics right now. This results in fewer wasted impressions, higher conversion rates, and a measurable drop in cost-per-acquisition. 

Related → Why Your ABM Is Only as Good as Your Target Account List | Demandbase

It Shrinks the Sales Cycle by Meeting Buyers Mid-Journey

B2B buyers are often 60-70% through their journey before they ever fill out a form or talk to a vendor. That means by the time they land in your CRM, they’ve already explored your competitors, formed opinions, and narrowed their options.

Intent-based marketing gives you the advantage of catching these buyers before they reach out. 

By monitoring behavioral signals like topic surges, competitor comparisons, or product-related keyword searches—you can identify which accounts are in research mode right now, even if they haven’t directly interacted with your brand. 

This early visibility allows you to intercept buyers mid-journey, while they’re still shaping their shortlist. Plus, it reduces the need for long nurture cycles since you already know what they want.

It Powers Personalized, Contextual Engagement

Buyers have already seen it all —templated messages, irrelevant ads to bait their attention, company-wide spam messages. As such, the usual generic “Hi {subject_name}…” won’t push past the spam folder. 

This is where intent data powers the conversation, giving you real-time data into what your target accounts are actively researching. 

Whether it’s a specific problem, competitor, or product category, you gain precise insight into what matters most to them right now. This allows you to deliver content and messaging that speaks directly to their current interests and pain points.

With intent data, you can:

• Craft emails that reference the exact topics or use cases an account is exploring
• Serve ads that align with the buyer’s research behavior or funnel stage
• Present landing pages or assets that match their level of urgency or awareness
• Adjust outreach based on the persona engaging (e.g., technical user vs. economic buyer)

The result is a more relevant, personalized experience at every touchpoint.

It Aligns Sales and Marketing Around Real Buying Signals

One of the most frustrating ROI-killers in B2B is the sales-marketing disconnect. 

Marketing runs campaigns, captures leads, and hands them off—only to see them ignored or deprioritized. Meanwhile, sales teams chase cold accounts or complain about lead quality.

Intent data solves this by creating a shared source of truth: concrete, behavioral signals that both teams can trust. 

Now, marketing can confidently say, “These are the accounts actively researching our category, comparing competitors, or engaging with buying-related content.” And sales knows exactly who to prioritize, and why, based on actual behavior.

Here’s an example of what that looks like: 

• Marketing builds targeted campaigns based on surge topics and account engagement
• Sales receives prioritized lists enriched with context: who’s showing intent, what they’re researching, and how recently

Both teams align on timing, messaging, and follow-up strategies based on where each account is in the journey.

It Future-Proofs Your GTM Strategy in a Privacy-First World

With  third-party cookies getting phased out, and agencies enforcing tighter data regulations (via GDPR and CCPA), traditional audience targeting is becoming less reliable. 

Intent-based marketing offers a smarter, privacy-compliant alternative. It leverages IP-based identification, contextual analysis, and shared intent data co-ops to surface buying signals from target accounts. 

This privacy-safe approach helps maintain compliance, ensuring you can continue identifying, prioritizing, and engaging buyers even without relying on cookies alone. 

Long-term, this adaptability translates into sustainable targeting strategies that won’t break every time Google or Apple updates their policies. 

Recommended → What The Heck Is A Go-To-Market (GTM) Strategy And What Do I Need To Know? 

It Enables Efficient Media Buying

Intent data empowers marketers to predict where the next deal is coming from. This lets you allocate budget dynamically and strategically. 

You can target specific intent topics, isolate late-stage researchers, and even tailor bids based on buying stage. You don’t have to pay premium CPMs across your entire audience, when you can bid smart and scale where it matters. 

This reduces your cost-per-lead, increases the efficiency of your ad spend, and maximizes the impact of each dollar invested in paid channels—whether that’s LinkedIn, programmatic, or content syndication.

Key Elements of an Effective Intent-Based Marketing Measurement Strategy

1. A Foundational Account-Based View

To truly evaluate performance, the foundation must shift from individual lead tracking to account-level measurement. 

That means reorienting your entire strategy—from engagement signals to pipeline metrics—around accounts, and not just the people inside them. 

Why This Matters

Intent signals aren’t always tied to a single known contact. They are collated based on the buying committee which comprises six to ten people that influences a deal. 

You might see surges in activity from a company, but not know exactly who within that company is researching. If you’re only looking at leads and form fills, you’ll miss the broader buying intent happening across the organization. 

However, by rolling up engagement data such as ads clicked, pages visited, content downloaded, third-party research activity, and even sales touchpoints—at the account level, you gain a complete understanding of whether the company as a whole is heating up. 

Example: Let’s say your intent platform shows that Company A has a high intent score for “cloud data integration.” You don’t yet have a form fill. But you notice the following:

• Four people from Company A visited your product pages in the past 10 days.
• Someone from a New York-based IP address (Company A’s HQ) downloaded a whitepaper on “Modernizing Cloud Infrastructure.”
• Your ad platform reports a 3x CTR from Company A’s domain over the last week.
• Intent data from a third-party publisher shows repeated visits to competitor comparison articles.

A lead-based model would likely fail to capture this as “qualified engagement.” 

But with an account-based view, you’re able to aggregate all of these signals, and classify it as a high-priority account entering an active research stage. This triggers a coordinated sales play and personalized marketing sequence. 

Related → Enterprise ABM Strategy: Modern Best Practices for Targeting High-Value Accounts 

2. Upper-Funnel Engagement and Influence

Once you’ve established an account-based foundation, the next layer is tracking upper-funnel engagement and influence. 

This means understanding who is engaging, how early they’re doing it—and what kind of influence those engagements have on moving accounts toward pipeline.

Why It Matters

Intent-based marketing allows you to get in front of buyers before they ever fill out a form. But if your measurement framework is only focused on last-touch or bottom-funnel conversion metrics (like demo requests or direct-response ads), you’ll miss out on ‘early influence.’

Most marketers ignore this stage in their attribution model because there’s often no hard conversion. But that doesn’t mean it didn’t have an impact.

Tracking and analyzing early interactions such as;

• anonymous visits to thought leadership content
• surges in third-party keyword research
• increased ad impressions and click-throughs
• repeat visits from the same IP group
• webinar signups or content downloads from unknown contacts

—helps you identify when an account is beginning to show interest before they declare it outright. 

Example: Let’s say you’re running an intent-driven campaign targeting CFOs and procurement leaders in the enterprise manufacturing sector. 

Your platform identifies three clusters of accounts showing surging intent for “spend optimization tools.”

You respond by:

• Serving educational video ads to those companies about procurement efficiency.
• Launching LinkedIn carousel posts featuring top industry challenges.
• Sending targeted content like benchmarking reports and third-party research to key buying roles.

None of these assets are designed to convert immediately. But:

• Ad view rates are high.
• Engagement time on your blog jumps 40%.
• Repeat visits from the same companies begin to show up in your analytics.
• Your sales team starts seeing warmer replies when reaching out.

With the right measurement strategy, this activity is captured and attributed to the account, informing your scoring models and pipeline attribution. That way, when these accounts finally do request a demo, you can clearly trace back the upper-funnel touchpoints that influenced their journey. 

Related → ABM Content Strategy: Top 3 Mistakes Marketers Make and How to Fix Them 

3. Mid-Funnel Pipeline Generation

Once upper-funnel engagement has been activated and nurtured, the focus shifts to how those intent-driven activities actually generate pipeline in the middle of the funnel. 

This stage is where intent data should clearly influence opportunity creation, account progression, and handoff between marketing and sales. 

Why It Matters

At the mid-funnel stage, your goal is to track how marketing-qualified accounts (MQAs) evolve into sales-qualified opportunities (SQOs) and whether your intent-driven touchpoints are responsible for moving the needle. 

This is where many teams fail. They might see increased engagement but fail to connect it to pipeline velocity. If you can’t measure that connection, it’s hard to prove ROI or optimize campaigns. 

Mid-funnel measurement helps you answer:

• Which accounts moved from MQA to opportunity because of intent-based campaigns?

• Did intent touchpoints accelerate the sales cycle?

• What intent signals were most common among accounts that converted?

• Are SDRs or AEs effectively following up on intent-qualified leads?

Example: Let’s assume you’re targeting accounts researching “enterprise expense automation.” Your intent platform (e.g., Demandbase) shows 300 accounts surging on that topic. 

You launch a multi-channel campaign:

• Email nurtures tailored to the finance persona.
• Case studies showcasing success in their industry.
• Retargeting ads that highlight product differentiators.
• SDR sequences triggered by specific keyword activity.

Over the next 6 weeks, you see:

• 85 of those accounts engage with the mid-funnel content.
• 30 accept sales outreach or book a meeting.
• 18 convert into pipeline opportunities.

With a solid measurement framework, you can quantify how many intent-identified accounts turned into real pipeline, what worked to move them forward, and where drop-offs occurred. 

Related → Different Types of Intent Signals for B2B Marketing | Demandbase 

4. Lower-Funnel Revenue Outcomes

This is where all your intent-based efforts either prove their value or fall short. 

Measuring lower-funnel revenue outcomes means connecting the dots between early intent signals, mid-funnel engagement, and closed-won deals. 

At this stage, you’re no longer tracking engagement or pipeline velocity alone. You’re measuring how much revenue intent marketing actually influenced and how predictably it can do so in the future. 

Why It Matters

The real business value of intent-based marketing is in accelerating deal velocity, increasing deal size, improving win rates, and lowering customer acquisition cost (CAC). 

These are the outcomes that get buy-in from leadership and secure long-term investment in your strategy. 

And because B2B sales cycles are long and complex, you need a clear system that tracks how intent-influenced accounts move through each stage until they generate booked revenue.

Example: Take for instance, your team uses Demandbase to identify a spike in activity around “cloud compliance automation” from mid-market tech firms. 

You run a focused campaign targeting 100 accounts with that specific surge, and after six months:

• 25 of those accounts enter pipeline
• 12 progress to proposal
• 7 close as deals

If each deal is worth $85,000, that’s $595,000 in sourced revenue directly traceable to a campaign initiated by third-party intent data. 

Recommended → Nailing the Numbers: The Reports Your CMO Wants to See

How to Determine the ROI of an Intent-Based Marketing Campaign

Evaluate Your Campaign Costs

You can’t know your return until you know your investment. Capturing every dollar spent ensures accuracy and helps you pinpoint which cost drivers to optimize.

Here’s what to include:

• Third-party intent platform fees (e.g., Demandbase)
• Ad spend (LinkedIn, programmatic, content syndication)
• Internal labor costs (marketing ops, SDR time)
• Martech expenses (CRM, attribution, enrichment tools)
• Creative and content production

You’ll need to sum all costs directly associated with the campaign. 

Example: $12,000 (platform fee) + $18,000 (ads) + $10,000 (SDR + marketing time) + $5,000 (tools)

Total Investment = $45,000

Attribute the Revenue Accurately

Once your campaign runs, tag and track:

• Accounts that engaged via intent triggers
• Campaigns they interacted with
• Opportunities created within your CRM
• Deals closed-won influenced or sourced by those activities

You can do this with UTM parameters, CRM campaign attribution, account-level activity timelines, and custom intent signal tagging in your pipeline reporting. 

Now sum the total closed-won revenue sourced or influenced. 

Example: 9 deals closed from the intent campaign, each worth $76,000

Total Revenue = $684,000 

Related → Revenue Marketing: Defined & Explained (+FAQs) 

Apply the ROI Formula

The classic ROI formula applies here: 

Example: = [($684,000 – $45,000) / $45,000] x 100  

= (639,000 / 45,000) x 100  

= 1420% ROI

This means that for every $1 you spent, you generated $14.20 in revenue. 

Analyze Supporting Metrics

Beyond basic ROI, these KPIs provide deeper insight:

Customer Acquisition Cost (CAC) 

Example: If you spent $100,000 on sales and marketing in Q2 and gained 200 new customers:

CAC = $100,000 / 200 = $500 per customer

Win Rate

Example: Let’s say your team had:

• 50 total opportunities in Q2
• 15 of those were won

Then:

• Win Rate = (15 / 50) x 100 = 30%

Sales Cycle Length

Example: Let’s assume you closed 5 deals over the past month with the following cycle times:

• Deal 1: 30 days
• Deal 2: 45 days
• Deal 3: 25 days
• Deal 4: 40 days
• Deal 5: 20 days

Total = 160 days

Number of deals = 5

Then:

• Sales Cycle Length = 160 / 5 = 32 days

So, your average sales cycle length is 32 days. 

Pipeline Velocity

Example: Let’s say:

• Qualified Opportunities = 40
• Win Rate = 25% → 0.25
• Average Deal Size = $10,000
• Sales Cycle = 30 days

Then:

Pipeline Velocity = (40 x 0.25 x $10,000) / 30 = $3,333/day

This means your pipeline is producing $3,333 in potential revenue per day. 

Average Deal Size

Example: If your sales team closed 10 deals this quarter, generating a total of $250,000 in revenue:

Average Deal Size = $250,000 / 10 = $25,000 

Customer Lifetime Value

Example: Let’s say:

• Average Revenue per Customer (monthly) = $100
• Gross Margin = 80%
• Churn Rate = 5% per month → Customer Lifetime = 1 / 0.05 = 20 months

Then:

LTV = $100 x 0.8 x 20 = $1,600

LTV-to-CAC Ratio 

Example: If:

• LTV = $3,000
• CAC = $1,000

Then:

LTV:CAC = $3,000 / $1,000 = 3:1

Best Practices for Measuring Intent-Based Marketing Campaign ROI

Track Intent Velocity and Time-to-Conversion

Beyond just who’s surging, ask: how fast are they moving through the funnel compared to non-intent accounts? 

One of the clearest ROI indicators of intent data is velocity—shorter deal cycles and faster engagement. Monitor time between first signal and first engagement, first engagement and meeting, and meeting to pipeline opportunity. 

If intent accounts are moving faster through each stage, you’re seeing measurable impact, even before revenue is closed. 

Compare Intent vs. Non-Intent Account Performance

Your strongest ROI signal comes from comparison. Take a segment of accounts showing strong intent activity and compare their performance (in terms of engagement, conversion rates, pipeline value, and deal velocity) to a matched control group of accounts without intent signals. 

This A/B-style approach reveals the true impact of intent activation across your funnel, offering a clear, data-backed case for continued investment in your strategy. 

Tie Intent Signals to Funnel Stages

Not all intent is equal. A spike in top-of-funnel topics like “CRM integrations” carries a very different weight than bottom-funnel searches like “best CRM for enterprise pricing.” 

To measure ROI effectively, map intent topics to funnel stages and apply weight accordingly. Then track how leads from each stage-based signal progress through your pipeline. 

This gives you insight into where intent creates the most leverage and where it may still need enablement or messaging refinement.

Monitor Sales Follow-Up Rates and Impact

Intent data only drives ROI when sales teams act on it. Monitor how often sales teams follow up with intent-identified accounts, how quickly they do it, and whether those follow-ups convert into meetings or pipeline. 

If sales isn’t using the data (or doesn’t know how) it limits your return. Run enablement sessions, give them intent “playbooks,” and track who’s following through. The tighter the marketing-to-sales execution loop, the higher the ROI. 

Related → How to Use Intent Data for B2B Sales and Marketing 

Integrate UTM and CRM Tracking Across Channels

To properly measure the ROI of intent activation, you need airtight tracking. Use UTM parameters on every ad, email, and link tied to intent campaigns. 

Then ensure your CRM is capturing and categorizing that data accurately. Build dashboards that tie those UTMs to revenue outcomes, such as meetings booked, opportunities created, and closed-won deals. 

Set Clear KPIs for Each Funnel Stage

Set performance KPIs for each intent stage. For example:

• Top-of-funnel: % of surging accounts reached, CTR on topic-based ads.
• Mid-funnel: % of surging accounts with active deals, meeting conversion rate.
• Bottom-funnel: Win rate for intent-qualified opportunities, deal velocity.

This granularity lets you track what’s working, where there’s leakage, and how to pivot. It also allows you to isolate which part of the intent journey is returning the most value and double down on it. 

Build ROI Models Around Influenced Pipeline

Intent often plays a bigger role in influencing deals than sourcing them outright. 

Instead of only tracking what deals originated from intent campaigns, also track what deals were influenced. This means an account that showed intent, received targeted messaging, and later became pipeline. 

GTM solutions like Demandbase can help here, allowing you to show contribution to pipeline and revenue in a multi-channel, multi-touch environment. 

Implement Multi-Touch Attribution with Intent Signal Weighting

Develop a custom attribution framework that assigns weighted values to different intent signals throughout the customer journey. 

In this case, a multi-touch attribution model (linear, time-decay, or data-driven) offers a better view into understanding how each touchpoint contributes to revenue, especially when intent signals are present across the journey. 

For example, a prospect downloading a technical whitepaper might receive a 15% attribution weight, while attending a product demo gets 35%. 

The key is mapping each touchpoint’s intent intensity and creating algorithmic models that reflect how different signals compound to drive conversion probability. 

Review and Refine ROI Metrics Quarterly

Market behavior shifts, signal quality evolves, and campaign tactics change. To measure ROI accurately over time, revisit your framework quarterly. Analyze what’s been working, where the bottlenecks are, and what new signals are emerging. 

ROI measurement is an iterative process, the more you refine it, the clearer the case for intent-based marketing becomes. 

Related → How to Measure Account-Based Marketing (+ABM Metrics)

Give Your Campaigns a Brain: Plug In Demandbase

Demandbase transforms your intent-based marketing by acting as the brain behind every campaign decision. 

Instead of guessing who’s ready to buy, Demandbase identifies real-time intent signals across the web, pinpoints which accounts are actively researching your solution, and dynamically adjusts your targeting, messaging, and spend accordingly.

Plugging Demandbase into your strategy means you’re running a system that learns, adapts, and optimizes with every interaction.

As Jared Levy, Growth Marketing Manager at League, puts it:

“With Demandbase, we effectively transformed advertising spend into qualified opportunities. Through precision targeting and actionable insights, we’ve strengthened cross-functional alignment, accelerated pipeline growth, and delivered measurable impact in the areas that matter most.”

Read Case Study →

Demandbase is built around one belief: that marketing works best when it’s precise, timely, and personal. 

Demandbase: Your Shortcut to Smarter ABM Wins →